scCAN: Single-Cell Clustering using Autoencoder and Network Fusion

A single-cell Clustering method using 'Autoencoder' and Network fusion ('scCAN') for segregating the cells from the high-dimensional 'scRNA-Seq' data. The software automatically determines the optimal number of clusters and then partitions the cells in a way such that the results are robust to noise and dropouts. 'scCAN' is fast and it supports Windows, Linux, and Mac OS.

Version: 1.0.4
Depends: R (≥ 3.5.0), scDHA, FNN, purrr
Imports: stats
Suggests: knitr
Published: 2022-04-06
Author: Bang Tran [aut, cre], Duc Tran [aut], Hung Nguyen [aut], Tin Nguyen [fnd]
Maintainer: Bang Tran <bang.t.s at>
License: LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL]
NeedsCompilation: no
Materials: README
CRAN checks: scCAN results


Reference manual: scCAN.pdf
Vignettes: scCAN


Package source: scCAN_1.0.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): scCAN_1.0.3.tgz, r-release (x86_64): scCAN_1.0.4.tgz, r-oldrel: scCAN_1.0.4.tgz
Old sources: scCAN archive


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